Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates.
Fairly Allocating Goods and (Terrible) Chores
Authors: Hadi Hosseini, Aghaheybat Mammadov, Tomasz Wąs
IJCAI 2023 | Venue PDF | LLM Run Details | Input Tokens: 19,947 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,941 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | By identifying a class of instances with terrible chores, we show that determining the existence of an EFX allocation is NP-complete. This result immediately implies the intractability of EFX under additive preferences. Nonetheless, we propose a natural subclass of lexicographic preferences for which an EFX and Pareto optimal (PO) allocation is guaranteed to exist and can be computed efficiently. |
| Researcher Affiliation | Academia | Hadi Hosseini , Aghaheybat Mammadov and Tomasz W as Pennsylvania State University EMAIL |
| Pseudocode | Yes | Algorithm 1 Finding an EFX and PO allocation for separable lexicographic preferences |
| Open Source Code | No | The paper does not provide an unambiguous statement or a direct link for open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper and does not use datasets for training or evaluation. |
| Dataset Splits | No | This is a theoretical paper and does not involve data splitting for validation. |
| Hardware Specification | No | This is a theoretical paper and does not describe computational experiments that would require hardware specifications. |
| Software Dependencies | No | This is a theoretical paper and does not mention specific software dependencies with version numbers for experimental replication. |
| Experiment Setup | No | This is a theoretical paper and does not describe experimental setups with hyperparameters or training configurations. |